In mammograms, a calcification is represented as small but brilliant white region of the digital image. Earlier detection of malignant calcifications in patients provides high expectation of surviving to this disease. Nevertheless, white regions are difficult to see by visual inspection because a mammogram is a gray-scale image of the breast. To help radiologists in detecting abnormal calcification, computer-inspection methods of mammograms have been proposed; however, it remains an open important issue. In this context, we propose a strategy for detecting calcifications in mammograms based on the analysis of the cluster prominence (cp) feature histogram. The highest frequencies of the cp histogram describe the calcifications on the mammography. Therefore, we obtain a function that models the behaviour of the cp histogram using the Vandermonde interpolation twice. The first interpolation yields a global representation, and the second models the highest frequencies of the histogram. A weak classifier is used for obtaining a final classification of the mammography, that is, with or without calcifications. Experimental results are compared with real DICOM images and their corresponding diagnosis provided by expert radiologists, showing that the cp feature is highly discriminative.

Optimization techniques are search methods, where the goal is to find a solution to an optimization problem, such that a given quantity is optimized, possibly subject to a set of constraints. Modern optimization techniques start to demonstrate their power in dealing with hard optimization problems in robotics and automation such as manufacturing cells formation, robot motion planning, worker scheduling, cell assignment, vehicle routing problem, assembly line balancing, shortest sequence planning, sensor placement, unmanned-aerial vehicles (UAV) communication relaying and multirobot coordination to name just a few. By example, in particle, path planning it is a difficult task in robotics, as well as construct and control a robot. The main propose of path planning is find a specific route in order to reach the target destination.

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Additive manufacturing has acquired a global industrial panorama for being an alternative to redirect the industry towards sustainability. However, previous studies have indicated that fused deposition modelling (FDM) techniques are potential sources of particles that are harmful to health. For this reason, this work is focused on exploring the behaviour and distribution of FDM resultant nanoparticles from the most commonly used printable materials through alternative methods as digital holographic microscopy (DHM). In this paper, we present the feasibility of using DHM to determine the presence of nanoparticles in the FDM process. Experimental results validate this technology’s precision and provide extensive knowledge about the implications of the FDM on health. The measure of the thin films deposited in glass substrates was between a minimum of 9 nm to a maximum of 200 nm, in agreement with the previous studies.